Knowledge and understandingYou should have a knowledge and understanding of the basic concepts of Artificial Intelligence including Search, Game Playing, KBS (including Uncertainty), Planning and Machine Learning.

Intellectual skillsYou should be able to use this knowledge and understanding of appropriate principles and guidelines to synthesise solutions to tasks in AI and to critically evaluate alternatives.

Practical skillsYou should be able to use a well known declarative language (Prolog) and to construct simple AI systems.

Transferable SkillsYou should be able to solve problems and evaluate outcomes and alternatives

3Attendance

You are expected to attend all the lectures. The lecture notes (see below) cover all the topics in the course, but these notes are concise, and do not contain much in the way of discussion, motivation or examples. The lectures will consist of slides (Powerpoint ), spoken material, and additional examples given on the blackboard. In order to understand the subject and the reasons for studying the material, you will need to attend the lectures and take notes to supplement lecture slides. This is your responsibility. If there is anything you do not understand during the lectures, then ask, either during or after the lecture. If the lectures are covering the material too quickly, then say so. If there is anything you do not understand in the slides, then ask.

In addition you are expected to supplement the lecture material by reading around the subject particularly the course text.

The art of creating machines that perform functions that require intelligence when performed by people. (Kurzweil)

The study of how to make computers do things at which, at the moment, people are better. (Rich and Knight)

9Systems that act like humans

You enter a room which has a computer terminal. You have a fixed period of time to type what you want into the terminal, and study the replies. At the other end of the line is either a human being or a computer system.

If it is a computer system, and at the end of the period you cannot reliably determine whether it is a system or a human, then the system is deemed to be intelligent.

10Systems that act like humans

The Turing Test approach

a human questioner cannot tell if

there is a computer or a human answering his question, via teletype (remote communication)

Progress goes in stages, following funding booms and crises Some examples

1. Machine translation of languages

1950s to 1966 - Syntactic translators

1966 - all US funding cancelled

1980 - commercial translators available

2. Neural Networks

1943 - first AI work by McCulloch Pitts

1950s 60s - Minskys book on Perceptrons stops nearly all work on nets

1986 - rediscovery of solutions leads to massive growth in neural nets research

The UK had its own funding freeze in 1973 when the Lighthill report reduced AI work severely -Lesson Dont claim too much for your discipline!!!!

Look for similar stop/go effects in fields like genetic algorithms and evolutionary computing. This is a very active modern area dating back to the work of Friedberg in 1958.

46Symbolic and Sub-symbolic AI

Symbolic AI is concerned with describing and manipulating our knowledge of the world as explicit symbols, where these symbols have clear relationships to entities in the real world.

Sub-symbolic AI (e.g. neural-nets) is more concerned with obtaining the correct response to an input stimulus without looking inside the box to see if parts of the mechanism can be associated with discrete real world objects.

This course is concerned with symbolic AI.

47AI Applications

Autonomous Planning Scheduling

Autonomous rovers.

48AI Applications

Autonomous Planning Scheduling

Telescope scheduling

49AI Applications

Autonomous Planning Scheduling

Analysis of data

50AI Applications

Medicine

Image guided surgery

51AI Applications

Medicine

Image analysis and enhancement

52AI Applications

Transportation

Autonomous vehicle control

53AI Applications

Transportation

Pedestrian detection

54AI ApplicationsGames 55AI Applications

Games

56AI Applications

Robotic toys

57AI Applications

Other application areas

Bioinformatics

Gene expression data analysis

Prediction of protein structure

Text classification, document sorting

Web pages, e-mails

Articles in the news

Video, image classification

Music composition, picture drawing

Natural Language Processing .

Perception.

58Homework

Read Pg (1 31) From the book

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